Mining Approximative Descriptions of Sets Using Rough Sets

Using concepts from rough set theory we investigate the existence of approximative descriptions of collections of objects that can be extracted from in data set, a problem of interest for biologists that need to find succinct descriptions of families of taxonomic units. Our algorithm is based on an anti-monotonicity of borders of object set and makes use of an approach that is, in a certain sense, a dual of the a priori algorithm used in identifying frequent item sets.